40 citations · 144 across the 31 of their papers we have counts for
6 papers · 1 filter
Constrained Dynamic Movement Primitives for Safe Learning of Motor Skills
Seiji Shaw, Devesh K. Jha, Arvind Raghunathan +4
Dynamic movement primitives are widely used for learning skills which can be demonstrated to a robot by a skilled human or controller. While their generalization capabilities and s…
Transformer Networks for Predictive Group Elevator Control
Jing Zhang, Athanasios Tsiligkaridis, Hiroshi Taguchi +2
We propose a Predictive Group Elevator Scheduler by using predictive information of passengers arrivals from a Transformer based destination predictor and a linear regression model…
Recursive McCormick Linearization of Multilinear Programs
Arvind U Raghunathan, Carlos Cardonha, David Bergman +1
Linear programming (LP) relaxations are widely employed in exact solution methods for multilinear programs (MLP). One example is the family of Recursive McCormick Linearization (RM…
Robust Pivoting: Exploiting Frictional Stability Using Bilevel Optimization
Yuki Shirai, Devesh K. Jha, Arvind Raghunathan +1
Generalizable manipulation requires that robots be able to interact with novel objects and environment. This requirement makes manipulation extremely challenging as a robot has to…
PYROBOCOP: Python-based Robotic Control & Optimization Package for Manipulation
Arvind Raghunathan, Devesh K. Jha, Diego Romeres
PYROBOCOP is a Python-based package for control, optimization and estimation of robotic systems described by nonlinear Differential Algebraic Equations (DAEs). In particular, the p…
Chance-Constrained Optimization in Contact-Rich Systems for Robust Manipulation
Yuki Shirai, Devesh K. Jha, Arvind Raghunathan +1
This paper presents a chance-constrained formulation for robust trajectory optimization during manipulation. In particular, we present a chance-constrained optimization for Stochas…